Abstract
나로우주센터의 발사통제시스템은 우주발사체의 비행궤적과 상태정보를 감시하기 위하여 지상추적시스템(추적레이더 2대, 원격자료수신장비 4대, 광학추적장비 1대)으로부터 정보를 받아 처리한다. 각 추적장치는 주로 다중경로나 클러터, 전파굴절에 의해 자체 오차를 나타내고 있어 전송된 정보들 중 하나만을 이용해서는 우주발사체의 실제 궤적을 판별할 수 없다. 본 논문에서는 취득된 추적자료의 후처리를 통해 우주발사체 비행궤적을 생성해내는 방법을 제시한다. 본 후처리 알고리즘은 크게 대기의 전파굴절에 따른 오차를 보정하는 부분과 다중센서 정보를 융합하는 부분으로 나뉘며, 효과적인 센서 융합을 위해 등가속 운동모델에 기반한 분산식 칼만필터를 구성하였다. 실측 자료의 후처리 적용 결과, 어떤 단일 센서에 의한 것 보다 오차가 최소화된 발사궤적을 얻을 수 있었다. For monitoring the flight trajectory and the status of a launch vehicle, the mission control system in NARO space center process data acquired from the ground tracking system, which consists of two tracking radars, four telemetry stations, and one electro-optical tracking system. Each tracking unit exhibits its own tracking error mainly due to multi-path, clutter and radio refraction, and by utilizing only one among transmitted informations, it is not possible to determine the actual vehicle trajectory. This paper presents a way of generating flight trajectory via post-processing the data received from the ground tracking system. The post-processing algorithm is divided into two parts: compensation for atmosphere radio refraction and multi-sensor fusion, for which a decentralized Kalman filter was adopted and implemented based on constant acceleration model. Applications of the present scheme to real data resulted in the flight trajectory where the tracking errors were minimized than done by any one sensor.
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